Repository Index

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

• rag
• tutorials
• langchain
• llama-index

This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security, vulnerability research, exploit development, reverse engineering, and more. 🔥 Also check: https://hackertraining.org

• hacking
• penetration-testing
• hacking-series
• cybersecurity

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.

• csharp
• java
• javascript
• mcp

Translated"Lee Hung-yi's Deep Learning Tutorial" (recommended by Professor Hung-yi Lee 👍, the Apple Book 🍎), PDF download address: https://github.com/datawhalechina/leedl-tutorial/releases

• machine-learning
• deep-learning
• leedl-tutorial
• cnn

Practice your pandas skills!

• pandas
• jupyter-notebooks
• pandas-tutorial
• python-pandas

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

• deep-learning
• mit
• self-driving-cars
• deep-reinforcement-learning

The codes I made while I practiced various TensorFlow examples

Code repository for The Automation Ahead series, showcasing practical examples for GenAI-driven automation in investments. Each installment dives into specific tools, techniques, and use cases to help professionals assess and apply GenAI effectively.

• data-science
• deep-learning
• finance
• financial-data

Exercises for the lecture "Selected Topics in Audio Signal Processing"